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40 lines
2.3 KiB
Markdown
40 lines
2.3 KiB
Markdown
# Qwen3-Next Usage
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SGLang has supported Qwen3-Next-80B-A3B-Instruct and Qwen3-Next-80B-A3B-Thinking since [this PR](https://github.com/sgl-project/sglang/pull/10233).
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## Launch Qwen3-Next with SGLang
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To serve Qwen3-Next models on 4xH100/H200 GPUs:
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```bash
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python3 -m sglang.launch_server --model Qwen/Qwen3-Next-80B-A3B-Instruct --tp 4
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```
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### Configuration Tips
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- `--max-mamba-cache-size`: Adjust `--max-mamba-cache-size` to increase mamba cache space and max running requests capability. It will decrease KV cache space as a trade-off. You can adjust it according to workload.
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- `--mamba-ssm-dtype`: `bfloat16` or `float32`, use `bfloat16` to save mamba cache size and `float32` to get more accurate results. The default setting is `float32`.
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- `--mamba-full-memory-ratio`: The ratio of mamba state memory to full kv cache memory. The default is 0.9.
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### Mamba Radix Cache
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SGLang supports prefix caching for Qwen3-Next models named `MambaRadixCache`, which improves inference speed by reusing computation results. There are two versions of `MambaRadixCache`:
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- `no_buffer`: The default version, which is also other hybrid linear models' choice. When it is enabled, SGLang will automatically close overlap schedule for compatibility reasons.
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- `extra_buffer`: An optimized version that is compatible with features like page size > 1, overlap schedule, and speculative decoding. It also supports storing mamba state in branching positions. However, it requires two extra mamba spaces for a ping-pong buffer for each request. To enable it, add the argument `--mamba-scheduler-strategy extra_buffer` when launching the server.
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### EAGLE Speculative Decoding
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**Description**: SGLang has supported Qwen3-Next models with [EAGLE speculative decoding](https://docs.sglang.io/advanced_features/speculative_decoding.html#EAGLE-Decoding).
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**Usage**:
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Add arguments `--speculative-algorithm`, `--speculative-num-steps`, `--speculative-eagle-topk` and `--speculative-num-draft-tokens` to enable this feature. For example:
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``` bash
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python3 -m sglang.launch_server \
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--model Qwen/Qwen3-Next-80B-A3B-Instruct \
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--tp 4 \
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--speculative-num-steps 3 \
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--speculative-eagle-topk 1 \
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--speculative-num-draft-tokens 4 \
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--speculative-algo NEXTN
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```
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Details can be seen in [this PR](https://github.com/sgl-project/sglang/pull/10233).
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